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Brad Abbott

Bio: Brad Abbott is an academic researcher from University of Oklahoma. The author has contributed to research in topics: Large Hadron Collider & Higgs boson. The author has an hindex of 137, co-authored 1566 publications receiving 98604 citations. Previous affiliations of Brad Abbott include Aix-Marseille University & Purdue University.


Papers
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Journal ArticleDOI
TL;DR: In this paper, a search for the direct pair production of a chargino and a neutralino was presented for a simplified supersymmetric model, where the final states considered for the search have large missing transverse momentum, an isolated electron or muon, and one of the following: either two jets identified as originating from bottom quarks, or two photons, or a second electron and muon with the same electric charge.
Abstract: A search is presented for the direct pair production of a chargino and a neutralino pp -> (X) over tilde (+/-)(1)(X) over tilde (0)(2), where the chargino decays to the lightest neutralino and the W boson, (X) over tilde (+/-)(1) -> (X) over tilde (0)(1) (W-+/- -> l(+/-)nu), while the neutralino decays to the lightest neutralino and the 125 GeV Higgs boson, (X) over tilde (0)(2) -> (X) over tilde (0)(1) (h -> bb/gamma gamma/l(+/-)nu qq). The final states considered for the search have large missing transverse momentum, an isolated electron or muon, and one of the following: either two jets identified as originating from bottom quarks, or two photons, or a second electron or muon with the same electric charge. The analysis is based on 20.3 fb(-1) of root s = 8 TeV proton-proton collision data delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with the Standard Model expectations, and limits are set in the context of a simplified supersymmetric model.

95 citations

Journal ArticleDOI
Georges Aad1, Brad Abbott2, Jalal Abdallah3, Ovsat Abdinov4  +2861 moreInstitutions (181)
TL;DR: In this paper, an analysis of events containing jets including at least one $b$-tagged jet, sizeable missing transverse momentum, and at least two leptons including a pair of the same electric charge, with the scalar sum of the jet and lepton transverse momenta being large.
Abstract: An analysis is presented of events containing jets including at least one $b$-tagged jet, sizeable missing transverse momentum, and at least two leptons including a pair of the same electric charge, with the scalar sum of the jet and lepton transverse momenta being large. A data sample with an integrated luminosity of 20.3 fb$^{-1}$ of $pp$ collisions at $\sqrt{s} = 8$ TeV recorded by the ATLAS detector at the Large Hadron Collider is used. Standard Model processes rarely produce these final states, but there are several models of physics beyond the Standard Model that predict an enhanced rate of production of such events; the ones considered here are production of vector-like quarks, enhanced four-top-quark production, pair production of chiral $b^\prime$-quarks, and production of two positively charged top quarks. Eleven signal regions are defined; subsets of these regions are combined when searching for each class of models. In the three signal regions primarily sensitive to positively charged top quark pair production, the data yield is consistent with the background expectation. There are more data events than expected from background in the set of eight signal regions defined for searching for vector-like quarks and chiral $b^\prime$-quarks, but the significance of the discrepancy is less than two standard deviations. The discrepancy reaches 2.5 standard deviations in the set of five signal regions defined for searching for four-top-quark production. The results are used to set 95% CL limits on various models.

95 citations

Journal ArticleDOI
Morad Aaboud, Alexander Kupco1, Samuel Webb2, Timo Dreyer3  +2977 moreInstitutions (217)
TL;DR: In this article, the efficiency of detecting b-hadrons was measured using a high purity sample of dileptonic top quark-antiquark pairs selected from the 36.1 fb$^{−1}$ of data collected by the ATLAS detector in 2015 and 2016 from proton-proton collisions produced by the Large Hadron Collider at a centre-of-mass energy of 13 $ TeV.
Abstract: The efficiency to identify jets containing b-hadrons (b-jets) is measured using a high purity sample of dileptonic top quark-antiquark pairs ( $ t\overline{t} $ ) selected from the 36.1 fb$^{−1}$ of data collected by the ATLAS detector in 2015 and 2016 from proton-proton collisions produced by the Large Hadron Collider at a centre-of-mass energy $ \sqrt{s}=13 $ TeV. Two methods are used to extract the efficiency from $ t\overline{t} $ events, a combinatorial likelihood approach and a tag-and-probe method. A boosted decision tree, not using b-tagging information, is used to select events in which two b-jets are present, which reduces the dominant uncertainty in the modelling of the flavour of the jets. The efficiency is extracted for jets in a transverse momentum range from 20 to 300 GeV, with data-to-simulation scale factors calculated by comparing the efficiency measured using collision data to that predicted by the simulation. The two methods give compatible results, and achieve a similar level of precision, measuring data-to-simulation scale factors close to unity with uncertainties ranging from 2% to 12% depending on the jet transverse momentum.

94 citations

Journal ArticleDOI
Georges Aad1, Brad Abbott2, Jalal Abdallah3, S. Abdel Khalek  +2948 moreInstitutions (211)
TL;DR: In this article, fiducial and differential cross-sections of Higgs boson production in the H -> ZZ* -> 4l decay channel are presented, based on 20.3 fb(-1) of pp collision data, produced at root s= 8 TeV centre-of-mass energy at the LHC and recorded by the ATLAS detector.

93 citations

Journal ArticleDOI
Georges Aad1, Alexander Kupco2, Bjørn Hallvard Samset3, P. Laurelli4  +2895 moreInstitutions (182)
TL;DR: In this article, the production cross sections of Upsilon(1S,2S,3S) mesons are reconstructed using the dimuon decay mode. And the results of the reconstruction are compared to several theoretical models of upsilon meson production, finding that none provide an accurate description of the data over the full range of Upsilicon transverse momenta accessible with this data set.
Abstract: Using 1.8 fb(-1) of pp collisions at a center- of- mass energy of 7 TeV recorded by the ATLAS detector at the Large Hadron Collider, we present measurements of the production cross sections of Upsilon(1S,2S,3S) mesons. Upsilon mesons are reconstructed using the dimuon decay mode. Total production cross sections for p(T) < 70 GeV and in the rapidity interval vertical bar y(Upsilon)vertical bar < 2. 25 are measured to be, 8.01 +/- 0.02 +/- 0.36 +/- 0.31 nb, 2.05 +/- 0.01 +/- 0.12 +/- 0.08 nb, and 0.92 +/- 0.01 +/- 0.07 +/- 0.04 nb, respectively, with uncertainties separated into statistical, systematic, and luminosity measurement effects. In addition, differential cross section times dimuon branching fractions for Upsilon(1S), Upsilon(2S), and Upsilon(3S) as a function of Upsilon transverse momentum pT and rapidity are presented. These cross sections are obtained assuming unpolarized production. If the production polarization is fully transverse or longitudinal with no azimuthal dependence in the helicity frame, the cross section may vary by approximately +/- 20%. If a nontrivial azimuthal dependence is considered, integrated cross sections may be significantly enhanced by a factor of 2 or more. We compare our results to several theoretical models of Upsilon meson production, finding that none provide an accurate description of our data over the full range of Upsilon transverse momenta accessible with this data set.

93 citations


Cited by
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Journal ArticleDOI

[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

Journal ArticleDOI
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

13,246 citations

Journal ArticleDOI
Claude Amsler1, Michael Doser2, Mario Antonelli, D. M. Asner3  +173 moreInstitutions (86)
TL;DR: This biennial Review summarizes much of particle physics, using data from previous editions.

12,798 citations

Journal ArticleDOI
01 Apr 1988-Nature
TL;DR: In this paper, a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) is presented.
Abstract: Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

9,929 citations